MSc in GIS at UCL PhD / Researcher at King’s College London The London Hybrid Exposure Model / Air quality GIS ‘stuff’ Now at Guy Carpenter (Model development, Re-insurance)
Exposure to particles on subway systems > important Seaton et al 2005, but … Tox. mechanisms Susceptible populations Analytical techniques
Measure variations in PM2.5 between lines and stations Characterise the chemical composition Calculate calibration factors for optical instruments Provide a spatially resolved dataset for future analysis
TSI AM510 SidePak (PM2.5) Philips Aerasense (numbers and size of particles) 31 hours All lines 89% of stations (NE Central, SW Piccadilly)
Need to link air quality measurements to locations No GPS signal on large sections of the network Considered using timetables / interpolating between known locations Ended up using a notepad
Tricky installation at Hampstead Particles collected on filters over 5 days measuring composition & amount High time resolution equipment installed Aethalometer / TSI Dustrak / 2 TSI Sidepaks / Micro-aethalometer
2015 tap in/tap out, Underground performance report Annual in/out for each station Mean PM2.5 measured at each station Passenger rank * air quality rank = passenger-weighted ranking
Linear model to calculate correction factors for mobile monitoring equipment Mobile monitoring equipment co-located in tube station v. outdoor
Particles tend to be larger in diameter than those at background or roadside environments More particles PM2.5 varied between lines & locations lowest Hammersmith & City (Mean 25 µg/m3), similar to roadside highest Victoria (381 µg/m3), 15 x higher than roadside
General relationship between ‘depth’ and air quality Oxford Circus, Waterloo, London Bridge, Victoria and Vauxhall at top of passenger-exposure ranking 79% of PM2.5 characterised 47% iron oxide, 7% elemental carbon, 11% organic carbon, 14% metallic and mineral oxides Previous studies using light-scattering may under-report PM
Characterise the remaining 11% More measurements accross the network to improve understanding train frequency passenger numbers time of year Interventions? Develop inclusion in exposure modelling